Robust sliding mode control for uncertain servo system using friction observer and recurrent fuzzy neural networks

被引：18

作者：

Han, Seong Ik ^{[2
]}

Jeong, Chan Se ^{[3
]}

Yang, Soon Yong ^{[1
]}

机构：

[1] Univ Ulsan, Dept Mech & Automot Engn, Ulsan 680749, South Korea

[2] Pusan Natl Univ, Sch Elect Engn, Pusan 609735, South Korea

[3] Univ Ulsan, Grad Sch Mech & Automot Engn, Ulsan 680749, South Korea

来源：

JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY | 2012年 / 26卷 / 04期

关键词：

LuGre friction model; Sliding mode control; Recurrent fuzzy neural networks; Adaptive friction estimator; Servo system; COMPENSATION; DRIVE;

D O I：

10.1007/s12206-012-0213-1

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

A robust positioning control scheme has been developed using friction parameter observer and recurrent fuzzy neural networks based on the sliding mode control. As a dynamic friction model, the LuGre model is adopted for handling friction compensation because it has been known to capture sufficiently the properties of a nonlinear dynamic friction. A developed friction parameter observer has a simple structure and also well estimates friction parameters of the LuGre friction model. In addition, an approximation method for the system uncertainty is developed using recurrent fuzzy neural networks technology to improve the precision positioning degree. Some simulation and experiment provide the verification on the performance of a proposed robust control scheme.

引用

页码：1149 / 1159

页数：11

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